TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics

Aleksei Dorkin, Kairit Sirts
7/4/2024
cs.CL

No confident code implementation found for this paper.

Abstract

We present our submission to the AXOLOTL-24 shared task. The shared task comprises two subtasks: identifying new senses that words gain with time (when comparing newer and older time periods) and producing the definitions for the identified new senses. We implemented a conceptually simple and computationally inexpensive solution to both subtasks. We trained adapter-based binary classification models to match glosses with usage examples and leveraged the probability output of the models to identify novel senses. The same models were used to match examples of novel sense usages with Wiktionary definitions. Our submission attained third place on the first subtask and the first place on the second subtask.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Word sense extension

83% match1 repo82023

To Word Senses and Beyond: Inducing Concepts with Contextualized Language Models

78% match1 repo2024

Explaining novel senses using definition generation with open language models

78% match2025

Graph-based Clustering for Detecting Semantic Change Across Time and Languages

78% match2024

Presence or Absence: Are Unknown Word Usages in Dictionaries?

78% match1 repo12024

Definition generation for lexical semantic change detection

78% match1 repo42024

Cite this paper

@article{dorkin2024tartunlp,
  title  = {TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics},
  author = {Aleksei Dorkin and Kairit Sirts},
  year   = {2024},
  eprint = {2407.03861},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.03861v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2407.03861.svg)](https://codeofpaper.com/paper/2407.03861)

Discussion